{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://mp.weixin.qq.com/s?__biz=MzkyMDMxNDkxOA==&mid=2247484512&idx=1&sn=37948397c7aad6d79bafd7764792dae7&chksm=c195f129f6e2783f04c6cd622d5686a03cc6255f8c0170d21b46882e8b90eb8373c54344a2e9&scene=178&cur_album_id=3447886516519747585#rd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 振动升降指标ASI策略.py\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from datetime import datetime\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_hist_k_data(code,start_date,end_date,frequency='d')->pd.DataFrame:\n",
    "    \"\"\"\n",
    "    获取历史K线数据\n",
    "    :return:\n",
    "    \"\"\"\n",
    "    import baostock as bs\n",
    "    bs.login()\n",
    "    rs = bs.query_history_k_data_plus(code,\"date,code,open,high,low,close,preclose,volume,amount,pctChg\",start_date,end_date,frequency=frequency)\n",
    "    data_list = []\n",
    "    while (rs.error_code == '0') & rs.next():\n",
    "        # 获取一条记录，将记录合并在一起\n",
    "        data_list.append(rs.get_row_data())\n",
    "    result = pd.DataFrame(data_list, columns=rs.fields)\n",
    "    result.open = result.open.astype(float)\n",
    "    result.high = result.high.astype(float)\n",
    "    result.low = result.low.astype(float)\n",
    "    result.close = result.close.astype(float)\n",
    "    result.date= pd.to_datetime(result.date)\n",
    "    result.set_index('date',inplace=True)\n",
    "    bs.logout()\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "login success!\n",
      "logout success!\n"
     ]
    }
   ],
   "source": [
    "# 获取股票数据\n",
    "stock_symbol = 'sz.000001'\n",
    "start_date = '2005-01-01'\n",
    "end_date = '2023-01-01'\n",
    "data = get_hist_k_data(stock_symbol, start_date, end_date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Dev\\AppData\\Local\\Temp\\ipykernel_24572\\1403390336.py:12: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!\n",
      "You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.\n",
      "A typical example is when you are setting values in a column of a DataFrame, like:\n",
      "\n",
      "df[\"col\"][row_indexer] = value\n",
      "\n",
      "Use `df.loc[row_indexer, \"col\"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "  data['Signal'][data['MTM'] > 0] = 1\n",
      "C:\\Users\\Dev\\AppData\\Local\\Temp\\ipykernel_24572\\1403390336.py:12: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  data['Signal'][data['MTM'] > 0] = 1\n",
      "C:\\Users\\Dev\\AppData\\Local\\Temp\\ipykernel_24572\\1403390336.py:14: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!\n",
      "You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.\n",
      "A typical example is when you are setting values in a column of a DataFrame, like:\n",
      "\n",
      "df[\"col\"][row_indexer] = value\n",
      "\n",
      "Use `df.loc[row_indexer, \"col\"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "  data['Signal'][data['MTM'] < 0] = -1\n",
      "C:\\Users\\Dev\\AppData\\Local\\Temp\\ipykernel_24572\\1403390336.py:14: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  data['Signal'][data['MTM'] < 0] = -1\n"
     ]
    }
   ],
   "source": [
    "# 计算动量指标MTM\n",
    "def calculate_mtm(data, period=14):\n",
    "    data['MTM'] = data['close'] - data['close'].shift(period)\n",
    "    return data\n",
    "\n",
    "# 生成交易信号\n",
    "data = calculate_mtm(data)\n",
    "data['Signal'] = 0\n",
    "data['Position'] = 0\n",
    "\n",
    "# 当MTM值从负变正时买入\n",
    "data['Signal'][data['MTM'] > 0] = 1\n",
    "# 当MTM值从正变负时卖出\n",
    "data['Signal'][data['MTM'] < 0] = -1\n",
    "\n",
    "# 计算持仓\n",
    "data['Position'] = data['Signal'].diff()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# 回测策略\n",
    "def backtest_strategy(data):\n",
    "    data['Strategy_Returns'] = data['Position'].shift(1) * data['close'].pct_change()\n",
    "    data['Cumulative_Returns'] = (1 + data['Strategy_Returns']).cumprod()\n",
    "    return data\n",
    "\n",
    "data = backtest_strategy(data)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1400x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制策略的累计收益\n",
    "plt.figure(figsize=(14, 7))\n",
    "plt.plot(data['Cumulative_Returns'], label='MTM Strategy')\n",
    "plt.title('MTM Strategy Cumulative Returns')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Cumulative Returns')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "tf",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
